1. BREEDING VALUE ESTIMATION FOR YIELD AND QUALITY TRAITS IN WHEAT USING BWGS PIPELINE
Gilles Charmet1*, Van Giang Tran1, Delphine Ly1 ,Jerome Auzanneau2
1INRA-Université Clermont II UMR1095 GDEC, Clermont-Ferrand, France
2Auzanneau J, Agri-Obtentions, La Minière, France

2. DURUM WHEAT IN FRANCE Worldwide ranking 5th (1st in EU)
2015 highest harvest: 40.8 Mt on 5.1 Mha
average yield 7.9 t/ha)
Average yield: ~7.5 t/ha
9 t/ha Pas de Calais
5 t/ha Gers
~5 millions hectares « conventionnal farming »
On average 6.3 pesticide
Tilling (55%), No-till (45%)
# 165 kg/ha mineral N
high yield
Lodging tolerance
Disease resistance
Protein content
High test weight
High bread making grade
DURUM
40000 hectares organic farming

3. Use of bread wheat in France

4. But wheat yields are stagnating in EU
Genetic progress must be speed up: needs for new methods

5. Coordination by UMR GDEC
Breeding for economically and environmentally sustainable wheat varieties: an integrated approach from genomics to selection
Coordination by UMR GDEC
26 partners (11 private)
124 permanent staff / 54 CDD
9 years
34 M€ (9 M€ granted)

6. Typical wheat breeding schemeF1 F2 F3 F4 F5 F6 F7 F8 F9
lines
10 years
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION

7. Typical wheat breeding scheme
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION
Typical wheat breeding scheme
Experiment /
traits
Loc No
remarks
Single plants
Visual trait
One
Low h²
# random selection
1-3 rows
Visual+diseases
1-2
Negative selection of worse rows/plants
Yield plots¨% protein
2-3, 1 rep
Yield plot % prot
Indirect Q test
5-8
2-4 rep
Accurate yield evaluation + GxL
Bread making
8-10
4 reps
Accurate yield + BM tests + G x Y
Official registration trials
12-15
T NT,LI
2 year official trials
BM test on year 1 harvest

8. Advantages of GS over phenotypic selection
h or prediction accuracy
Genetic variability: can be monitored by markers
DG = i h sG / L
Cycle length: can be
Shortenned by juvenil
Selection and intermating
Selection intensity:
Can be increased if
Genotyping cost < phenotyping

9. Where to insert GS in a wheat
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION
Where to insert GS in a wheat
breeding scheme ?
DG = i h sG / L

10. BWGS pipeline V2.0: General structure
Dimentional reduction
Imputation of genotypes
Comparison of models (cross-validation)
Optimal models
GEBV
Training genotypic data
Training phenotypic data
Target phenotypic data
Cor (y, GEBV)
MSEP, SD (yhat)
bwgs.selgen.cv(…)
bwgs.predict(…)
quality indicators

11. BWGS pipeline V2.0: General structureTh

12. An application to INRA-AO real winter wheat breeding programme:
Preliminary results
Jérôme AUZANNEAU
AGRI OBTENTIONS

13. Genotyping: The BreedWheat 420K SNP Axiom chip
13,670 validated SNPs
Genotyping: The BreedWheat 420K SNP Axiom chip
139,904 genic SNPs
140,450 intergenic SNPs
105,577 ISBP-SNPs
9,570 candidate gene SNPs
4,815 Axiom-validated SNPs
Illumina Infinium 90K chip
5,155 Axiom-validated SNPs
4,120 validated SNPs
124 major gene SNPs
423,385 SNPs
SNP
QC+pol
genic
InterG
MAF >0.01
genic SNP
Inter Genic
Random sampling

14. Use of historical data Crossa et al 2010, Dawson et al 2013, Rutkoski et al 2015)
BLUE lmer(Y~geno+(1|year:site:trial:bloc)+(1|year:site:geno),data=…)
BLUP lmer(Y~(1|year:site:trial:bloc)+(1|geno)+(1|year:site:geno),data=Y)
Cor (YieldBLUP, YieldBLUE)=0.94
Yield, protein: records/ 1589 lines (760 Genotyped)
Fusarium HB: records, 1705 lines (672 G)
Bread-making traits: 5887records / 526 lines (357 G)

15. Preliminary analyses: Influence of marker no and training size (Yield, GBLUP)

16. Héritability and prediction accuracy GBLUP – 10 000 random markers

17. Relationship h²- r(y,GEBV)

18. Comparing accuracy among methods Yield, N=760, 10 000 markers

19. Comparing predictions among methods Yield, N=760, 10 000 markers
Cor (GEBV RKHS, GEBV GBLUP)= 0.92

20. DG = i h sG / L Propose new schemes? Crosses: 10² 2-3 years F2 bulks
Select parents on GEBV per se of expected progeny BV
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION
Select parents
crosses
F2 or DH
Apply GS
2-3 years
Cycles GS
Use historical data for training
DG = i h sG / L
Adapted from J Hickey
EUCARPIA Biometrics in Plant Breeding 2015

21. Take home messages Cost of genotyping: unafordable on 105 candidates
New schemes to be explored
Maintainance of accuracy across # germplasms?
GxE and multitrait methods to be further developped (e.g. Jarquin et al 2014, Heslot et al 2014)
Important LD in breeding pop: few 1000s markers needed
Historical data useful for training
GEBV accurate enough to enable efficient GS
Few differences among methods for accuracy and prediction

22. Aknowledgements Programming DATA ANALYSES Advises, comments G Charmet
INRA GDEC

23. Thank you for your attention